The invention relates to a method for correcting single-pixel noise defects in a two-dimensional camera pixel field through assigning to such pixel defect a multi-pixel environment for therefrom deriving an interpolated substitute pixel value as being recited in the preamble of claim 1. Such cameras pixel fields come with increasingly large numbers of pixels, and have currently exceeded the 1 Mpixel watermark. A discomfort in the use of such cameras are various categories of faulty pixels, and in particular such pixels that are unsteady, although not being limited thereto: sometimes they fail and sometimes they are correct. Furthermore, any correction that is effected should take care to maintain as much from the image information as possible. In particular, the applying of a standard and spatially uniform low pass filter would destroy many a crisp detail from a costly image.
Prior art has recognized that in certain situations the original pixel value should be retained. In particular, the United States Patent Application Publication 2001/0055428 discloses a method for diminishing noise in a megapixel environment, and through assessing a subject pixel and pixel data around it selects either the original pixel, or alternatively, the mean value of subject pixel and environment. However, the present inventor has recognized that even if corrected, the correction should be based on such operations that would not introduce extraneous deviations, and thus the environment that is taken into account for such a relatively simple approach should be screened for acceptability, as it were.
In general, noise reduction algorithms for image applications assume that the signal has a high local correlation. They use some form of spatial averaging to minimize the noise. This will effectively remove so-called speckles, that are image pixels that exhibit a large deviation from surrounding pixels. However, this procedure will also diminish some high frequency components in an image. For a speckle, this will blur the defect out over several pixels depending on the correction kernel size.
Another method uses adaptive noise filtering with a threshold, to determine which pixels in the kernel to use for low-pass filtering. This method preserves high frequency signal components whilst minimizing unwanted noise. However, upon meeting a speckle, the mechanism in question is hardly able to reduce the error intensity, because there are no amplitudes corresponding to the speckle, in particular, when the kernel has a reasonable size such as 5×5 pixels. This approach will then usually retain the original speckle value.